Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “composite power system”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

Semiconductor nanocrystal photocatalysis for the production of solar fuels

Colloidal semiconducting nanocrystals (NCs) are powerful elements of a photocatalytic system useful for enabling a variety of chemical transformations owing to their strong light-absorbing properties and high degree of size-, shape-, and composition-tunability. Key to their utility is our understanding of the photoinduced charge transfer processes required for these photochemical transformations. This Perspective will focus on the implementation of semiconductor NCs for photochemical fuel formation. Three general system designs for photocatalytic proton reduction using semiconductor NCs will be reviewed: metal–semiconductor heterostructures, NC photosensitizers with molecular catalysts, and hydrogenase-based systems. Additionally, other relevant reactions toward solar fuel targets, such as CO 2 and N 2 reductions with NCs, will also be highlighted. Illustrating the versatile roles that NCs can play in light-driven chemical reactions, advances made toward NC-catalyzed organic transformations will be discussed. Finally, we will share a few concluding thoughts and perspectives on the future of the field, with a focus on goals toward improving and implementing NC-based technologies for solar fuel development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2.2.2.405 - Verdant/NREL Research Measurement Campaign

The marine renewable energy industry primarily uses thermoset composite materials for blades and other hydrodynamic components, which can have up to 50% reduction in strength when exposed to seawater and are not recyclable. Thermoplastic composite materials have been shown at a coupon-scale to have improved seawater saturated properties but have not been validated at full scale. The primary goal of the project is to demonstrate the structural properties of thermoplastic-fiberglass composite blades compared to epoxy-fiberglass composite blades in seawater at a tidal energy site on an operational turbine. Through this work, NREL manufactured, tested and deployed thermoplastic blades and a data acquisition system on Verdant Power's turbine TriFrame in the East River, NYC. The thermoplastic blades and DAQ were retrieved after a 6-month deployment with no signs of degradation and all cable connections, structural supports and strain gages had a 100% survival rate. The blades are currently undergoing post-deployment structural validation to compare their performance to traditional epoxy blades that were deployed for the same amount of time. This will increase confidence in thermoplastic materials and move it closer to commercial adoption, as well as increase confidence in the design of a DAQ and instrumentation method for a tidal turbine. However, due to an error in the DAQ software that was introduced after the DAQ and software were validated, there was no loads data collected during the deployment.

blade testing↗

The Novel Hybrid Ab Initio Model of High-Performance Structural Alloys Design for Fossil Energy Power Plants

The current project developed a novel HT-CALPHAD/DFT approach, which can quickly design new high-performance structural alloys for the application of FE power plants. The PI will mainly take charge of high-throughput DFT simulations and computational thermodynamics of the selected multicomponent alloy systems for the FE power plant applications. At the end of the project, a novel hybrid model based on high throughput CALPHAD/DFT simulations and computational thermodynamics will be developed to provide guidance on how to identify multi-component new high-performance structural alloys with much less computational effort needed. It will address the extensive computation time needed for DFT on the new alloys design. In addition, it will also address the well-known headache of DFT, i.e. how to make the accurate prediction of the high-temperature equilibria. The novel hybrid model the PI proposed will not only be applied to the design of high-performance structural alloys in FE power plants but in many different applications, such as nuclear reactors. This hybrid modeling approach includes four sections: 1) HT-CALPHAD modeling of Al-Co-Cr-Ni-Fe system with FCC and BCC phase. In this section, 3561 non-equiatomic compositions were randomly generated in order to investigate the phase stability of single FCC and BCC phases. Meanwhile, we proposed a data screening procedure to screen out the good candidates within these compositions, considering the temperature range, average density, and melting temperature, etc. 2) Investigation of FCC-Cr lattice stability in Fe-Cr system. We systematically assessed the reliability of FCC-Cr lattice stability derived by DFT and CALPHAD approaches. Meanwhile, the Fe-Cr binary system was chosen as a case study to verify the Cr lattice stability obtained by both approaches. 3) High-throughput DFT modeling on elastic properties of Al-Co-Cr-Ni-Fe systems. We predicted and established the FCC quinary elastic constant database of the Al-Co-Cr-Fe-Ni systems at 0K by using special quasi-random structure (SQS) approach. The predictions will start with pure elements of Al-Co-Cr-Fe-Ni system and will be continued with binaries, ternaries, quaternaries, and finally the quinary compositions. 3) Modeling of temperature-dependent elastic properties in Al-Co-Cr-Ni-Fe systems. In this part, we predict the thermal expansion coefficient and elastic stiffness coefficient as a function of temperature by applying quasiharmonic approximation. With this approach, the elastic properties of HEAs at elevate temperature can be estimated.

01 COAL, LIGNITE, AND PEAT↗

AMES: MS and MENG in Advanced Manufacturing for Energy at the University of Connecticut (Final Technical Report)

The objective of the project is to develop and implement an advanced degree program (MS and MENG in Advanced Manufacturing for Energy Systems, AMES) responding to the long-term workforce and technology requirements of the nation’s advanced energy products manufacturing industry. The program provided an industry relevant research experience by leveraging existing energy (e.g. fuels, power electronics, electrochemical power sources) and advanced manufacturing (e.g. additive manufacturing, composites, sensing) research at UConn funded by federal and state agencies, and industry, as well as through our industry partnerships. The trainees have joined research teams, advised by faculty with relevant research interests and expertise and were co-advised by industrial mentors. The AMES program have developed a truly interdisciplinary curriculum, first graduate degree program at UConn School (now College) of Engineering not housed in an academic department, with concentrations focusing on various challenges in advanced manufacturing for energy systems, e.g. advanced materials and processing. The project also developed new courses focusing on common technical and professional skills, and integrated various components for an industry relevant training. The program has admitted 29 Master of Science (MS) students since inception in January 2019. Twenty six of these students were AMES fellows, who have received partial funding from DoE through this project. The program far exceeded the goal of admitting at least five new MS (with thesis) students. All students were required to complete a thesis (M.S.) or a capstone (M.Eng.) project that are defined in collaboration with industry partners to ensure industrial relevancy, addressing a current industrial challenges. Industrial mentors also participated in advising the students in their research. AMES fellows, in addition were also required to complete an industrial internship for further industrial experience.

36 MATERIALS SCIENCE↗

A Coacervate-Based Mixed-Conducting Binder for High-Power, High-Energy Batteries

Polymer binders add crucial structural integrity to lithium ion battery composite cathodes, but industry standard binders, such as polyvinylidene fluoride (PVDF), are insulating to ions and electrons, detrimentally adding resistance to the overall system. In this work, we use electrostatics to stabilize a blend of a charged conjugated polymer with an oppositely charged polyelectrolyte, providing a processable, stable binder with high ionic and electronic conduction. Using LiFePO4 cathodes as a model system, we show significant improvement in rate capability and stability, with the conducting binder enabling a 39% utilization at 6C compared to 1.6% when PVDF is the binder. Additionally, the conducting binder affords a 63% capacity retention over 400 C/2 cycles, compared to only a 6% retention over 400 cycles when PVDF is the binder. These results show that electrostatically stabilized complexation is a promising strategy to integrate both electronic and ionic conductivity into a binder, while simultaneously maintaining stability and processability.

36 MATERIALS SCIENCE↗

Temperature Inhibition of Plasma-Driven Methane Conversion in DBD Systems

Low-temperature non-thermal plasmas produce highly reactive chemical environments made up of electrons, ions, radicals, and vibrationally excited molecules. These reactive species, when combined with catalysts, can help drive thermodynamically unfavorable chemical reactions at low temperatures and atmospheric pressure. The conversion of methane (CH 4 ) to produce other value-added chemicals is a good model system because of its applicability to a wide range of industries. To effectively create these plasma catalytic systems, a fundamental understanding of the plasma-phase chemistry alone is imperative. While there have been many studies on methane plasmas and how certain operating conditions (i.e., gas composition and power) affect the plasma, there is limited understanding on how changing bulk reaction temperature affects the plasma properties and ensuing plasma chemistry. Here, in this work, we use a dielectric barrier discharge to investigate the effects of temperature on the reaction chemistry and the plasma’s electrical properties in various methane-gas mixtures. Results show that increasing temperature leads to a reduction in methane conversion as well as changes to both the gas and dielectric material pre-breakdown, which manifests itself in temperature-dependent electrical properties of the plasma. Experiments at various temperatures and power show a positive correlation between key electrical plasma properties (average charge and lifetime per filament) and the measured methane conversion as a function of temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Harnessing the Power of Machine Learning and Omics to Identify Environmental Regulation on Microbial Functional Composition for Soil C, N, and P Cycling

Microbial enzyme-mediated soil organic matter (SOM) decomposition regulates many key ecosystem functions, such as elemental cycling, soil carbon sequestration, and soil fertility. However, representing microbial processes in Earth system models (ESMs) remains challenging due to a limited understanding of the spatial patterns of diverse microbial functions responsible for soil carbon (C), nitrogen (N), and phosphorus (P) cycling as well as the underlying mechanisms regulating their relative abundances across various environments. We collected published metagenomics data across the continental US (CONUS) to identify hundreds of microbial genes involved in soil C, N, and P cycling and grouped them into eight enzyme functional classes (EFCs). Each EFC represented a group of gene-encoded potential enzymes that decompose similar soil compounds. By integrating the abundances of omics-informed EFCs with the corresponding environmental information, we trained a machine learning (ML) model to identify key edaphic, climate, and vegetation factors regulating the abundances of each EFC. Quantitative analysis of effects of these factors revealed that the spatial distribution of eight EFCs for soil C, N, and P cycling across CONUS reflected potential resource optimization strategies of microbial communities under nutrient limitation, preferential organic-mineral associations, and climatological stresses. This insight, together with the interpreted ML tool and the CONUS-level benchmark for EFCs abundances, paves the way for parameterizing environmental-regulated microbial functional dynamics in biogeochemical models.

machine learning↗

Submerged Fatigue Testing of Marine Energy Advanced Materials

Marine energy structures are typically made of advanced composite materials and are subjected to extreme ocean environments in service. In extreme ocean environments, seawater currents and waves load structures repeatedly, which cause two environmental conditions: water intrusion and mechanical fatigue. In prior research, the two environmental conditions were applied sequentially, where composite specimens were aged and then mechanically tested. To understand the combined effects of dynamic loading and water intrusion on composite materials, the present study involves the static and fatigue four-point bend testing of composite coupons in a water tank. The water tank was designed and built to fit either a 100 kN or a 250 kN load frame. Flexural strength value, cycles to failure, and failure mode results from submerged fatigue testing will be used to inform marine energy structure designs. The coupon-scale test method will be used to scale up to and inform methods for subsequent subcomponent testing and standards development. The benefits of designing marine energy structures to informed standards are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

composite materials↗

Effects of Coatings on Water Intrusion and Strain Gauge Durability in Submerged Fatigue Conditions: Preprint

Marine energy structures are typically made using composite materials and are repeatedly loaded by currents and waves. Submersion and repeated loading lead to two environmental effects: moisture intrusion and mechanical fatigue. To understand the combined effects of moisture intrusion and mechanical fatigue on marine energy structures, submerged fatigue testing can be used. Submerged fatigue testing often requires submerged instrumentation to validate component manufacturing methods and models. Measuring strain is critical for understanding marine energy component loads. One common method for measuring strain is by using foil strain gauges, but the durability of strain gauges in submerged fatigue conditions was not well-understood. To increase strain gauge durability and protection from contamination, delamination, and water intrusion, strain gauge coatings may be applied over strain gauges and wire connections. In this study, strain gauges were adhered to composite coupons, coated, and mechanically tested in a water tank. Cycles to composite failure, cycles to strain gauge failure, strains, and strain gauge failure modes were used to measure the effects of strain gauge coatings on composite fatigue life and strain gauge durability. The methods developed and measurements taken at the coupon scale in this study will be used to inform methods and designs for subsequent submerged subcomponent testing, full-scale testing, and standards development. The benefits of designing marine energy structures to informed standards and designs are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

composite fatigue testing↗

Effects of Synthesis Gas Concentration, Composition, and Operational Time on Tubular Solid Oxide Fuel Cell Performance

There is tremendous potential to utilize the exhaust gases and heat already present within combustion chambers to generate electrical power via solid oxide fuel cells (SOFCs). Variations in system design have been investigated as well as thorough examinations into the impacts of environmental conditions and fuel composition/concentration on SOFC performance. In an attempt to isolate the impacts of carbon monoxide and hydrogen concentration ratios within the exhaust stream, this work utilizes multi-temperature performance analyses with simulated methane combustion exhaust as fuel combined with dilute hydrogen baseline tests. These comparisons reveal the impacts of the complex reaction pathways carbon monoxide participates in when used as an SOFC fuel. Despite these complexities, performance reductions as a result of the presence of carbon monoxide are low when compared to similarly dilute hydrogen as a fuel. This provides further motivation for the continued development of SOFC-CHP systems. Stability testing performed over 80 h reveals the need for careful control of the operating environment as well as signs of carbon deposition. As a result of gas flow disruption, impacts of anode oxidation that may normally not hinder power production become significant factors in addition to coarsening of the anode material. Thermal management and strategies to minimize these impacts are a topic of future research.

54 ENVIRONMENTAL SCIENCES↗

Data-Centric Approach to Capture Non-Polynomial Nonlinear Dynamics

We propose an analytical construction of observable functions in the extended dynamic mode decomposition (EDMD) algorithm. EDMD is a numerical method for approximating the spectral properties of the Koopman operator. The choice of observable functions is fundamental for applying EDMD to nonlinear problems arising in systems and control. Existing methods either start from a set of dictionary functions and look for the subset that best fits the underlying nonlinear dynamics or rely on machine learning algorithms to “learn” observable functions. Conversely, in this paper, we start from the dynamical system model and lift it through the Lie derivatives, rendering it into a polynomial form. This proposed transformation into a polynomial form is exact and provides an adequate set of observable functions. The strength of the proposed approach is its applicability to a broader class of nonlinear dynamical systems, particularly those with nonpolynomial functions and compositions thereof. Moreover, it retains the physical interpretability of the underlying dynamical system and can be readily integrated into existing numerical libraries. We demonstrate the proposed approach with an application to electric power systems. The modeled system consists of a single generator connected to an infinite bus, where nonlinear terms include sine and cosine functions. The results demonstrate the effectiveness of the proposed procedure in off-attractor nonlinear dynamics for estimation and prediction; the observable functions obtained from the proposed construction outperform methods that use dictionary functions comprising monomials or radial basis functions.

extended dynamic mode decomposition↗

Nodal Capacity Expansion Modeling with ReEDS: A Case Study of the RTS-GMLC Test System

Test systems play an important role in power systems analysis and are used extensively for a wide range of purposes like reliability analysis, production cost modeling, studying the impacts of load shifting, and many more. These test systems have continued to evolve over the years to keep pace with changing system compositions due to technology and policy changes. In this work, we apply the Regional Energy Deployment System (ReEDS) model, a large-scale capacity expansion model (CEM), on the nodal RTS-GMLC system to perform capacity expansion of the bus-level test system. This work both demonstrates that a large-scale CEM can successfully be applied to nodal systems, and that the CEM can allow a test system to be evolved to meet desired criteria. The process allowed the coupling of CEM data not available in the test system (such as capital costs) with test system data to provide plausible system evolutions in line with scenario specifications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

CIGS Technology Advancement via Fundamental Modeling of Defect/Impurity Interactions (Final Technical Report)

The primary goals of the proposed work were to provide modeling tools (and the associated insight which comes along with model development) for design and optimization of CuIn x Ga 1-x Se 2 (CIGS) and CdSeTe (CST) solar cell manufacturing processes and to establish the foundation for comprehensive end-to-end predictive modeling tools to enable optimization of thin film photovoltaic technology for performance, cost, yield, and reliability. The initial focus of efforts within this project was to develop coupled process/optical/device models for CIGS PV technology and to work with Siva Power to apply that TCAD (technology computer-aided design) system to improve the efficiency and reduce manufacturing costs for CIGS solar cells. Our approach to that end was to generate an extensive database of DFT calculations and to use those calculations via statistical thermodynamics methods and Monte Carlo simulation to develop and characterize models for the behavior of native defects as well as intentional and unintentional impurities, including the redistribution of the primary components of CIGS films. Increased effort went toward coupling those models for defect behavior and composition evolution to the performance of multicrystalline CIGS solar cells via prediction of doping level and recombination lifetime as function of manufacturing process. In the second budget period, the project pivoted to developing a similar system for the CdSeTe system, focused especially on understanding the role of Se/Te alloy concentration. Execution of the project resulted in the successful development of TCAD systems for both CIGS and CdSeTe thin film PV within the Synopsys Sentaurus framework by utilizing the Alagator interface. In the first budget period of the project, we developed quantitative models for the major components of CIGS PV and implemented them within a framework that couples process, optical, and device simulation. From the insights we have gained, we identified novel opportunities for enhancing CIGS solar cell performance and have laid the groundwork to further optimize the layer structure, composition profile, and thermal cycles for substantially improved efficiency and lower manufacturing costs. For the CIGS system, process changes to achieve greater than 1% absolute enhancement in efficiency were identified, but testing of those approaches was stymied by lack of a domestic CIGS manufacturing partner after the closure of Siva Power as well as Miasole. For CdSeTe, a fully capable TCAD system only became ready to apply near the end of the project period, so substantial opportunities remain to apply those models to enhance the leading thin film PV technology.

14 SOLAR ENERGY↗

The past, present, and future of peaking thermal power plants in the United States

Today's power systems rely on "peaker plants" to reliably serve load during peak demand periods. In this study we consider the present competitiveness of different peaking options, how much and what kinds of plants have provided U.S. peaking capacity, and potential future peaking fleet compositions. We explore how capital intensity impacts the breakeven capacity factor between two potential resources: combustion turbines (CTs) and combined cycle plants (CCs). CTs outcompete CCs below 12%-17% annual capacity factor at today's prices, but can shift with changes to fuel or start costs. Historically, gas CTs and petroleum steam plants most closely fit the role of peakers. Peaking capacity could grow from approximately 280 GW today to 460-770 GW in 2050 composed of a wider range of resources. We conclude by discussing implications of this shift, with a focus on the potential planning considerations for shifting to a greater utilization of CCs for peaking needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Geometry, Disorder and Phase Transitions in Topological States of Matter

The quantum Hall effect is the birthplace of topological states of matter, a major theme at the forefront of condensed matter physics in the past two decades. The fractional quantum Hall (FQH) effect revolutionized our understanding of phases of electronic matter. FQH states support exotic fractionally charged excitations that obey Abelian or non-Abelian fractional statistics, which are topological excitations that result from the underlying topological order. During this project, our group discovered a previously unrecognized geometric degree of freedom of incompressible FQH states and studied that for a variety of gapped FQH states. We brought this new concept into direct contact with experiments for the first time by generalizing it to Fermi-liquid states of composite fermions. Using the newly formulated powerful infinite Density Matrix Renormalization Group method, our numerical calculations yielded a parameter free prediction that was found to be in excellent agreement with experimental findings on electron systems in semiconductor heterostructures. In parallel, we performed extensive numerical studies on different, competing phases at various Landau level filling factors, and quantum phase transitions that result from such a competition, e.g. Abelian-non-Abelian phase transitions in bilayer systems. We studied geometrical excitations dubbed “gravitons” (because of their analogy with excitations in the theory of gravitation) and ways to excite and detect them, and explored how they couple with topological excitations. In graphene-based chiral materials, we realized the ability to tune through different incompressible and compressible states in a single Landau level, and found appropriate experimental parameters for the exploration of universal Luttinger liquid behavior not obtained in semiconductor-based electron systems. We showed that topological systems had a very different response from nontopological systems to strong disorder (many-body localization) as well as periodic drives.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Feasibility of fusion plasma burn control via real-time, sub-divertor neutral gas isotopic and compositional analysis

The ability to provide fusion burn control without requiring physical access through the first wall and fuel breeding blankets, would be vital for any future, magnetically confined fusion power reactor. A multi-sensor, fusion fuel cycle exhaust, neutral gas analysis system on JET, capable of delivering real time data, and accessing only the sub-divertor region, provides an excellent example of such capability. Optimized for and operated during the deuterium–tritium experimental campaigns 2 and 3 (DTE2, DTE3), it is proving valuable for planning to explore fusion reactor burn control in ITER with a comparable diagnostic system called the Diagnostic Residual Gas Analyzer (DRGA). This paper aims to show feasibility of developing model-based controllers for ITER and next generation, reactor-relevant devices, by building both on the empirical experience in JET-DTE2, and on the already emerging experience on developing such models specifically for ITER. The paper begins with a specific use-case from JET-DTE2, pertaining to the observed sensitivity of the fusion neutron yield on the concentration of isotopic helium-3 ( 3 He), with data from one of the high-performance DT shots exhibited with emphasis on the 3 He measurement via the sub-divertor. Then, a first model is developed and then explored with simulations that aim to discover how well the controllers in the model react to either insufficient levels of 3 He or excessive levels of 3 He. The simulations then explore potential impact from a delay in the measurement (or the response) that would be comparable to the ∼1 s, conductance limited response for the ITER DRGA system, currently in its final design. The simulations show that control is feasible, and that its effectiveness is not significantly impacted by such delay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Structural Testing Technology Development: Cooperative Research and Development Final Report, CRADA Number CRD-06-00200

NREL is the only organization in the US that is accredited to conduct tests of wind turbine systems and components in accordance with International Electrotechnical Commission (IEC) test standards. The National Wind Technology Center houses the only full-scale wind turbine blade drivetrain test facilities in the US. To maintain these facilities, accreditation, and the acceptance of the wind industry, NREL must strive continuously to maintain and improve staff capabilities, procedures, facility and equipment. In addition, as wind turbines continue to increase in size, NREL must improve its capability to test the larger components associated with these new turbines. NREL is currently investigating methods to increase blade and drivetrain testing capabilities. Mitsubishi Power Systems (MPS) must also strive to meet the demands of the evolving wind energy industry by developing, proving and manufacturing new, cost-effective blades for its turbines. Mitsubishi has established a joint venture with TPI composites of Rhode Island for manufacturing blades to be installed on US wind turbines. There is an obvious advantage to test these prototype blades in a US facility. The NREL blade test facility is uniquely capable of fulfilling this need. In addition, NREL can provide other testing support to MPS through the use of its dynamometer facility for drivetrain testing and through the use of NREL’s field-testing capabilities for testing wind turbine systems. This CRADA provides the opportunity for both organizations to achieve critical goals in development of wind energy in the US. MPS obtains verification of its wind turbine components and system. NREL obtains improved test capabilities.

17 WIND ENERGY↗